Improving driver safety with artificial intelligence and machine learning

AI and machine learning are no longer the stuff of fiction, they are actively transforming how we live and do business in many different industries, including fleet management. We may not realise it, but these digital tools are all around us. They analyse how we shop online, stream entertainment, and operate vehicles, then adapt to our changing behaviours to suggest new purchases, new entertainment choices, and to keep drivers safe.

These artificial Intelligence systems can process information and adapt to promote change faster than any one person, or even a team of people, ever could. This speed is essential when a driver’s life could be on the line. The safety of drivers should be your number one priority for your fleet operations. According to The Bureau of Infrastructure, Transport and Regional Economics (BITRE) 216 people died in 2017 from 196 fatal crashes involving heavy vehicles in Australia.

Artificial intelligence systems act to bring this number down in some large trucks, service vehicles, and passenger vehicles by gathering information on how we drive and teaching themselves to recognise new risks on the road. They can then alert drivers to danger or even assist in controlling the vehicle to avoid it.

Companies in our industry are using predictive analytics as a way of applying artificial intelligence and machine learning to improve the safety of their drivers. Artificial intelligence can indicate that a driver has a high likelihood of being involved in a preventable crash, allowing the company the opportunity to mitigate that potentially catastrophic event.

Your back-office can apply intelligence to data gathered from across your fleet to analyse driving behaviour and performance, then give timely, advice to coach for safer and more efficient driving.

Originally published by here.

Contact Market Motion if you would like more information on how fleets of all sizes can benefit from artificial intelligence and machine learning.